Data annotation - Merge clusters


library(Seurat)
Registered S3 method overwritten by 'data.table':
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Registered S3 method overwritten by 'htmlwidgets':
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  print.htmlwidget tools:rstudio
Seurat v4 was just loaded with SeuratObject v5; disabling v5 assays and validation
routines, and ensuring assays work in strict v3/v4 compatibility mode
library(tidyverse)
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library(CelltypeR)
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Attaching package: ‘CelltypeR’

The following object is masked from ‘package:ggplot2’:

    annotate

Read in the step7 object

nsc <- readRDS("/Users/rhalenathomas/Documents/Data/scRNAseq/ADHD_ZNZ_Mcgill/ADHDresultsFeb10/NSC/step7/objs7/seu_step7.rds")
Warning message:
R graphics engine version 15 is not supported by this version of RStudio. The Plots tab will be disabled until a newer version of RStudio is installed. 

See the Dimplot

DimPlot(nsc, group.by = 'integrated_snn_res.0.25', label = TRUE) 


DimPlot(nsc, group.by = "Celltypes1", label = TRUE)

#DimPlot(nsc, group.by = "Celltypes2", label = TRUE)
#DimPlot(nsc, group.by = "CelltypesMain", label = TRUE)
DimPlot(nsc, group.by = "CelltypesMain2", label = TRUE)

#DimPlot(nsc, reduction = "umap", label = TRUE, pt.size = 0.1, raster = FALSE) 
NPC_glia <- FindMarkers(nsc, ident.1 = "NPC_glia", ident.2 = c("Progenitors", "NPC"), only.pos = TRUE)

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View(Neurons_sub)
View(NPC_markers)

Name Fibroblast as Glia Keep NPC-glia Change Precursor vs NPC

NSC-vas is now NSC-APOA1 NSC- SOX2

NPC-MEF2C Progen is really NPC-POU5F1 NPC-S100B

Neurons-DCX (was neurons) Neurons-GRIA1 (was excitatory neurons)

See the neurons object


fcn <- readRDS("/Users/rhalenathomas/Documents/Data/scRNAseq/ADHD_ZNZ_Mcgill/ADHDresultsFeb10/FCN/step7/objs7/seu_step7.rds")

Transfer lables predictions

need to match version 4 and version 5 seurat

Myanchors <- FindTransferAnchors(reference = MBO ,query = fcn, dims = 1:30)
Performing PCA on the provided reference using 1076 features as input.
Projecting cell embeddings
Error in UseMethod(generic = "GetAssayData", object = object) : 
  no applicable method for 'GetAssayData' applied to an object of class "Assay5"

Visualize expression


proliferation = c("PCNA","MKI67")
neuralstem = c("SOX2","NES","PAX6","MASH1")

DotPlot(fcn, features = proliferation, group.by = "integrated_snn_res.0.25")

FeaturePlot(fcn, features = proliferation)

neuralstem = c("SOX2","NES","PAX6","MASH1")

DotPlot(fcn, features = neuralstem, group.by = "integrated_snn_res.0.25")
Warning in FetchData.Seurat(object = object, vars = features, cells = cells) :
  The following requested variables were not found: MASH1

FeaturePlot(fcn, features = neuralstem)
Warning in FetchData.Seurat(object = object, vars = c(dims, "ident", features),  :
  The following requested variables were not found: MASH1

# simplify cell types 1
cluster.ids<-c("Differentating_to_neurons", "NSC", "NSC", "Neurons", "Endothelial", "Endothelial", "Endothelial", "NSC", "Neuroblasts", "Neurons") 
  Idents(fcn) <- 'integrated_snn_res.0.25'
  names(cluster.ids) <- levels(fcn)
  fcn <- RenameIdents(fcn, cluster.ids)
  fcn <- AddMetaData(object=fcn, metadata=Idents(fcn), col.name = "CelltypesMain1")

DimPlot(fcn, label = TRUE, group.by = "CelltypesMain1")

NA
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---
title: "R Notebook"
output: html_notebook
---

Data annotation - Merge clusters

```{r}

library(Seurat)
library(tidyverse)
library(CelltypeR)

```


Read in the step7 object

```{r}
# NSC

nsc <- readRDS("/Users/rhalenathomas/Documents/Data/scRNAseq/ADHD_ZNZ_Mcgill/ADHDresultsFeb10/NSC/step7/objs7/seu_step7.rds")
colnames(nsc@meta.data)
# add my annotations made earlier 
table(nsc$Rhalena_pool1_obj_2_predictions,nsc$integreted_snn_res.0.25)

annotations <- c("ExNeurons","Fibroblasts","Neurons","Progen-Div","NSC-div","NSC-div-ki67","NPC-glia",
                 "NPC-glia-div","NPC","NeuronsChol","NSC-vasculature","NPC-cortical")
cluster.ids<-c("Excitatory_neurons", "Fibroblasts", "Neurons", "Progenitor_div", "NSC_div", "NSC_div_KI67", "NPC_glia", "NPC_div_glia", "NPC", "Cholinergic_neurons", "NSC_vasculature", "NPC_cortical")
# add annotations
  Idents(nsc) <- 'integrated_snn_res.0.25'
  names(cluster.ids) <- levels(nsc)
  nsc <- RenameIdents(nsc, cluster.ids)
  nsc <- AddMetaData(object=nsc, metadata=Idents(nsc), col.name = "Celltypes1")
  
  
  
  
cluster.ids<-c("Neurons", "Glia", "Neurons", "NSC", "NSC", "NSC", "NPC-glia", "NPC-glia", "NPC", "Neurons", "NSC", "NSC")
 
    Idents(nsc) <- 'integrated_snn_res.0.25'
  names(cluster.ids) <- levels(nsc)
  nsc <- RenameIdents(nsc, cluster.ids)
  nsc <- AddMetaData(object=nsc, metadata=Idents(nsc), col.name = "CelltypesMain")
   
 
  
cluster.ids<-c("Neurons", "Glia", "Neurons", "Progenitor_div", "NSC_div", "NSC_div_KI67", "NPC_glia", "NPC_div_glia", "NPC", "Neurons", "NSC_vasculature", "NPC_cortical")   
    
cluster.ids<-c("Neurons_Ex", "Fibroblasts", "Neurons", "Progenitors", "NSC", "NSC", "NPC_glia", "Progenitors", "NPC", "Neurons", "NSC_vasculature", "NSC") # Cell types simplified

cluster.ids<-c("Neurons", "Fibroblasts", "Neurons", "Progenitors", "NSC", "NSC", "NSC", "Progenitors", "NPC", "Neurons", "NSC_vasculature", "NSC") # Cell types most simplified

 

cluster.ids<-c("Neurons_Ex", "Fibroblasts", "Neurons", "Progenitors", "NSC", "NSC", "NPC_glia", "Progenitors", "NPC", "Neurons", "NSC_vasculature", "NSC") # Cell types simplified
  Idents(nsc) <- 'integrated_snn_res.0.25'
  names(cluster.ids) <- levels(nsc)
  nsc <- RenameIdents(nsc, cluster.ids)
  nsc <- AddMetaData(object=nsc, metadata=Idents(nsc), col.name = "CelltypesMain2")
   
    
    

```


See the Dimplot

```{r}
DimPlot(nsc, group.by = 'integrated_snn_res.0.25', label = TRUE) 

DimPlot(nsc, group.by = "Celltypes1", label = TRUE)
#DimPlot(nsc, group.by = "Celltypes2", label = TRUE)
#DimPlot(nsc, group.by = "CelltypesMain", label = TRUE)
DimPlot(nsc, group.by = "CelltypesMain2", label = TRUE)
#DimPlot(nsc, reduction = "umap", label = TRUE, pt.size = 0.1, raster = FALSE) 

```


```{r}

Idents(nsc) <- "CelltypesMain2"
table(nsc$CelltypesMain2)
unique(nsc$CelltypesMain2)
nsc_sub <- FindMarkers(nsc, ident.1 = "NSC_vasculature", ident.2 = "NSC", only.pos = FALSE)

write.csv(nsc_sub, "subtypeMarkers_NSCvasVS_NSC.csv")


NPC_markers <- FindMarkers(nsc, ident.1 = "NPC", ident.2 = c("NPC_glia", "Progenitors"), only.pos = TRUE)
Progenitor_markers <- FindMarkers(nsc, ident.1 = "Progenitors", ident.2 = c("NPC_glia", "NPC"), only.pos = TRUE)
NPC_glia <- FindMarkers(nsc, ident.1 = "NPC_glia", ident.2 = c("Progenitors", "NPC"), only.pos = TRUE)

Neurons_sub <- FindMarkers(nsc, ident.1 = "Neurons", ident.2 = "Neurons_Ex", only.pos = FALSE)



```

Name Fibroblast as Glia
Keep NPC-glia
Change Precursor vs NPC

NSC-vas is now NSC-APOA1
NSC- SOX2

NPC-MEF2C
Progen is really NPC-POU5F1
NPC-S100B

Neurons-DCX   (was neurons)
Neurons-GRIA1 (was excitatory neurons)

See the neurons object


```{r}

cluster.ids<-c("Neurons-GRIA1", "Glia", "Neurons-DCX", "NPC-POU5F1", "NSC-SOX2", "NSC-SOX2", "NPC-S100B", "NPC-POU5F1", "NPC-MEF2C", "Neurons-DCX", "NSC-APOA1", "NSC-SOX2") # Cell types simplified
  Idents(nsc) <- 'integrated_snn_res.0.25'
  names(cluster.ids) <- levels(nsc)
  nsc <- RenameIdents(nsc, cluster.ids)
  nsc <- AddMetaData(object=nsc, metadata=Idents(nsc), col.name = "CelltypesFinal")
  
DimPlot(nsc, group.by = "CelltypesFinal", label = TRUE)
  
  
```





```{r}

fcn <- readRDS("/Users/rhalenathomas/Documents/Data/scRNAseq/ADHD_ZNZ_Mcgill/ADHDresultsFeb10/FCN/step7/objs7/seu_step7.rds")
```

```{r}
DimPlot(fcn)
DimPlot(fcn, label = TRUE)

#fcn$integrated_snn_res.0.25
```

```{r}

an <- get_annotation(fcn, seu.cluster =  fcn$RNA_snn_res.0.25,seu.label = fcn$Rhalena_pool1_obj_annot2_predictions,top_n = 5, Label = "Predicted")

tb <- as.data.frame(table(fcn$integrated_snn_res.0.25,fcn$Rhalena_pool1_obj_annot2_predictions))
tb



```


Transfer lables predictions

# need to match version 4 and version 5 seurat

```{r}


```






```{r}
# this is the reference data
MBO <- readRDS("/Users/rhalenathomas/Documents/Data/scRNAseq/AST23_BrainComm/MBOclusters_names29072021.rds")

Idents(MBO) <- "cluster_labels"

DefaultAssay(MBO) <- "RNA"
DefaultAssay(fcn) <- "integrated"
# find the reference anchors
print("finding reference anchors")
Myanchors <- FindTransferAnchors(reference = MBO ,query = fcn, dims = 1:30)
# can try a range of dims 20-50
print("getting predictions")
predictions <- TransferData(anchorset = Myanchors, refdata = MBO$cluster_labels)
fcn <- AddMetaData(fcn, metadata = predictions)


print(table(MO.query$predicted.id))
```


Visualize expression 


```{r}

earlyNeur = c("DCX","NEUROD1","TBR1")

DefaultAssay(fcn) <- "integrated"
FeaturePlot(fcn, features = earlyNeur)
DotPlot(fcn, features = earlyNeur, group.by = "integrated_snn_res.0.25")

```

```{r}

proliferation = c("PCNA","MKI67")
neuralstem = c("SOX2","NES","PAX6","MASH1")

DotPlot(fcn, features = proliferation, group.by = "integrated_snn_res.0.25")
FeaturePlot(fcn, features = proliferation)

```
```{r}
neuralstem = c("SOX2","NES","PAX6","MASH1")

DotPlot(fcn, features = neuralstem, group.by = "integrated_snn_res.0.25")
FeaturePlot(fcn, features = neuralstem)

```

```{r}
# Try some first draft annotations
# rough annotations


cluster.ids<-c("Differentating_to_neurons", "Prolifer_NeuralStem", "NPC", "Neurons_modulator", "Endo_Glia", "Endo_RG", "Endo_neuroblasts", "NPC_RG_dividing", "RG_neural", "Neurons") 
  Idents(fcn) <- 'integrated_snn_res.0.25'
  names(cluster.ids) <- levels(fcn)
  fcn <- RenameIdents(fcn, cluster.ids)
  fcn <- AddMetaData(object=fcn, metadata=Idents(fcn), col.name = "Celltypes1")

DimPlot(fcn, label = TRUE, group.by = "Celltypes1")

```

```{r}
# simplify cell types 1
cluster.ids<-c("Differentating_to_neurons", "NSC", "NSC", "Neurons", "Endothelial", "Endothelial", "Endothelial", "NSC", "Neuroblasts", "Neurons") 
  Idents(fcn) <- 'integrated_snn_res.0.25'
  names(cluster.ids) <- levels(fcn)
  fcn <- RenameIdents(fcn, cluster.ids)
  fcn <- AddMetaData(object=fcn, metadata=Idents(fcn), col.name = "CelltypesMain1")

DimPlot(fcn, label = TRUE, group.by = "CelltypesMain1")



```


